Drag on two co-axial rigid spheres moving normal to a plane: Newtonian and Carreau fluids

The boundary effect and the presence of a nearby entity on the drag of a rigid entity is investigated by considering the movement of two identical, rigid, coaxial spheres normal to a plane in both a Newtonian and a Carreau fluid at a low to medium large Reynolds number. The parameters key to the phenomenon under consideration, including the nature of the fluid, the separation distance between two spheres, the distance between the near sphere and the plane, and the Reynolds number, on the drag coefficient are discussed. We show that the influence of a boundary on the drag coefficient is more important than that of the nature of a fluid and that of the separation distance between two spheres. The variation of the drag coefficient as a function of Reynolds number for a Carreau fluid is similar to that for a Newtonian fluid. Due to the shear-thinning nature of the former the drag coefficient in the former is smaller than that in the latter. The influence of the index parameter of a Carreau fluid becomes appreciable only if the Carreau number is sufficiently large. Correlations between the drag coefficient and the key parameters of a system are developed for the case when the Reynolds number is smaller than l.     

Improved DV-Hop based on parallel and compact whale optimization algorithm for localization in wireless sensor networks

Wireless Networks - Improving localization performance is one of the critical issues in Wireless Sensor Networks (WSN). As a range-free localization algorithm, Distance Vector-Hop(DV-Hop) is...     

Economic lot sizing in a production system with random demand

An extended economic production quantity model that copes with random demand is developed in this paper. A unique feature of the proposed study is the consideration of transient shortage during the production stage, which has not been explicitly analysed in existing literature. The considered costs include set-up cost for the batch production, inventory carrying cost during the production and depletion stages in one replenishment cycle, and shortage cost when demand cannot be satisfied from the shop floor immediately. Based on renewal reward process, a per-unit-time expected cost model is developed and analysed. Under some mild condition, it can be shown that the approximate cost function is convex. Computational experiments have demonstrated that the average reduction in total cost is significant when the proposed lot sizing policy is compared with those with deterministic demand.     

Hadamard transform based fast codeword search algorithm for high-dimensional VQ encoding

An efficient nearest neighbor codeword search algorithm for vector quantization based on the Hadamard transform is presented in this paper. Four elimination criteria are derived from two important inequalities based on three characteristic values in the Hadamard transform domain. Before the encoding process, the Hadamard transform is performed on all the codewords in the codebook and then the transformed codewords are sorted in the ascending order of their first elements. During the encoding process, firstly the Hadamard transform is applied to the input vector and its characteristic values are calculated; secondly, the codeword search is initialized with the codeword whose Hadamard-transformed first element is nearest to that of the input vector; and finally the closest codeword is found by an up-and-down search procedure using the four elimination criteria. Experimental results demonstrate that the proposed algorithm is much more efficient than the most existing nearest neighbor codeword search algorithms in the case of problems of high dimensionality.     

Bidirectional Transmission Using Tunable Fiber Lasers and Injection-Locked Fabry–PÉrot Laser Diodes for WDM Access Networks

We propose and demonstrate the use of fiber ring lasers and Fabry-Perot laser diodes (FP-LDs) for wavelength-division-multiplexing access networks. The fiber ring laser not only generates downstream data traffic but also serves as the wavelength-selecting injection light source for the FP-LD located at the subscriber site. Moreover, it is wavelength tunable and can be applied to dynamic wavelength assignment networks. The ring laser has a tunable range of 30 nm in the C-band and a power fluctuation smaller than 0.6 dB. For 10-Gb/s downstream and 1.25-Gb/s upstream transmissions over 10-km single-mode fiber, power penalties less than 0.9 and 0.5 dB are demonstrated, respectively. A 40-dB sidemode suppression ratio is obtained for the FP-LD injection-locking at 1544.8 nm.     

A superior linearization method for signomial discrete functions in solving three-dimensional open-dimension rectangular packing problems

This article studies the three-dimensional open-dimension rectangular packing problem (3D-ODRPP) in which a set of given rectangular boxes is packed into a large container of minimal volume. This problem is usually formulated as a mixed-integer nonlinear programming problem with a signomial term in the objective. Existing exact methods experience difficulty in solving large-scale problems within a reasonable amount of time. This study reformulates the original problem as a mixed-integer linear programming problem by a novel method that reduces the number of constraints in linearizing the signomial term with discrete variables. In addition, the range reduction method is used to tighten variable bounds for further reducing the number of variables and constraints in problem transformation. Numerical experiments are presented to demonstrate that the computational efficiency of the proposed method is superior to existing methods in obtaining the global optimal solution of the 3D-ODRPP.     

Monkey King Evolution: an enhanced ebb-tide-fish algorithm for global optimization and its application in vehicle navigation under wireless sensor network environment

Optimization algorithms are proposed to maximize the desirable properties while simultaneously minimizing the undesirable characteristics. Particle Swarm Optimization (PSO) is a famous optimization algorithm, and it has undergone many variants since its inception in 1995. Though different topologies and relations among particles are used in some state-of-the-art PSO variants, the overall performance on high dimensional multimodal optimization problem is still not very good. In this paper, we present a new memetic optimization algorithm, named Monkey King Evolutionary (MKE) algorithm, and give a comparative view of the PSO variants, including the canonical PSO, Inertia Weighted PSO, Constriction Coefficients PSO, Fully-Informed Particle Sawrm, Cooperative PSO, Comprehensive Learning PSO and some variants proposed in recent years, such as Dynamic Neighborhood Learning PSO, Social Learning Particle Swarm Optimization etc. The proposed MKE algorithm is a further work of ebb-tide-fish algorithm and what’s more it performs very well not only on unimodal benchmark functions but also on multimodal ones on high dimensions. Comparison results under CEC2013 test suite for real parameter optimization show that the proposed MKE algorithm outperforms state-of-the-art PSO variants significantly. An application of the vehicle navigation optimization is also discussed in the paper, and the conducted experiment shows that the proposed approach to path navigation optimization saves travel time of real-time traffic navigation in a micro-scope traffic networks.     

Hybrid algorithm optimization for coverage problem in wireless sensor networks

Telecommunication Systems - With the continuous development of evolutionary computing, many excellent algorithms have emerged, which are applied in all walks of life to solve various practical...     

A parallel compact cat swarm optimization and its application in DV-Hop node localization for wireless sensor network

Wireless Networks - Cat swarm optimization (CSO) has been applied to a variety of fields because of the better capacity of searching for optimum and higher robustness. However, the poor convergency...